Loading libraries & data, and adding some metadata
pikes_data <- read_csv("data/PP_raman_data.csv")
## Parsed with column specification:
## cols(
## Sample_Name = col_character(),
## grain = col_double(),
## `Spot number` = col_double(),
## FWHM = col_double(),
## raman_shift = col_double()
## )
evans_data <- read_csv("data/ME_Raman Data.csv")
## Parsed with column specification:
## cols(
## Sample_Name = col_character(),
## grain = col_character(),
## `Spot number` = col_double(),
## FWHM = col_double(),
## raman_shift = col_double()
## )
Nasdala_idealized_line <- read_csv("data/Nasdala.csv")
## Parsed with column specification:
## cols(
## Nasdala_FWHM = col_double(),
## Nasdala_shift = col_double()
## )
pikes_zhe <- read_csv("data/Pikes_Data_for_R .csv")
## Parsed with column specification:
## cols(
## Sample = col_character(),
## Grain = col_character(),
## Elevation = col_double(),
## Corr_Date = col_double(),
## eU = col_double(),
## eU_unc = col_double(),
## Corr_date_unc = col_double(),
## r = col_double(),
## Mass = col_double(),
## length = col_double(),
## FT = col_double(),
## U = col_double(),
## Th = col_double(),
## Sm = col_double(),
## He = col_double(),
## Raw_date = col_double()
## )
Modify the sample names for ease of reading, where PP stands for Pikes Peak, ME stands for Mt. Evans. Samples are numbered from 1 - 6 with the lowest elevation sample being 1 and highest elevation sample being.
pikes_data <- pikes_data %>%
mutate (
Peak = "Pikes Peak",
papername =
ifelse(Sample_Name == "PP2084", "PP1", #If True, add label PP2
ifelse( Sample_Name == "PP2479", "PP2", #If True, add label PP2
ifelse (Sample_Name == "PP2907", "PP3", #If true, add label PP3
ifelse (Sample_Name == "PP3597", "PP4", #If true, add label PP4
ifelse (Sample_Name == "PP3971", "PP5", "PP6") #if true, add label PP5, ELSE add the label PP6
)
)
)
)
)
evans_data <- evans_data %>% mutate(
Peak = "Mount Evans",
papername = ifelse (Sample_Name == "ME10", "ME1_2872",
ifelse (Sample_Name == "ME8", "ME2_3596",
ifelse (Sample_Name == "ME3", "ME3_3978",
"ME4_4345")
)
)
)
pikes_zhe <- pikes_zhe %>% mutate (
Peak = "Pikes Peak",
papername =
ifelse(Sample == "PP2084", "PP1", #If True, add label PP2
ifelse( Sample == "PP2479", "PP2", #If True, add label PP2
ifelse (Sample == "PP2907", "PP3", #If true, add label PP3
ifelse (Sample == "PP3597", "PP4", #If true, add label PP4
ifelse (Sample == "PP3971", "PP5", "PP6") #if true, add label PP5, ELSE add the label PP6
)
)
)
)
)
Some very light statistics
This chunk uses the raman_summary function that can be found in the scripts folder in the “Custom Functions.R” file
pikes_flatlist <- pikes_data %>%
group_by(papername, grain) %>%
raman_summary()
view(pikes_flatlist)
evans_flatlist <- evans_data %>%
group_by(papername, grain) %>%
raman_summary()
view(evans_flatlist)
dated_grains <- pikes_flatlist %>%
filter (papername == "PP1") %>%
filter (grain == 23 | grain == 31 | grain == 32 | grain == 33 | grain == 36) %>%
select (grain, FWHM_median, FWHM_sd)
## Adding missing grouping variables: `papername`
dated_grains <- dated_grains %>%
bind_rows(
pikes_flatlist %>%
filter (papername == "PP3") %>%
filter (grain == 17 | grain == 21 | grain == 27) %>%
select (grain, FWHM_median, FWHM_sd)
)
## Adding missing grouping variables: `papername`
dated_grains %>% ggplot() + aes (FWHM_median, FWHM_sd, color = papername) + geom_point() + theme_figure() + scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,12))
Main text figures
#Figure 2a
evans_violin <- evans_data %>%
filter(papername != "NA") %>%
ggplot()+
geom_violin(aes(papername, FWHM, fill = Sample_Name), scale = "count", na.rm = TRUE, draw_quantiles = c(0.25, 0.5, 0.75))+
scale_fill_manual(values = c("#FDE0A1", "#782281", "#EA5661"))+
scale_y_continuous(expand = c(0,0), limits = c(0,36))+
ylab(TeX('$\\FWHM (cm^{-1})')) +
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
legend.position = "none",
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
print(evans_violin)
#Figure 2b
evans_grain_summary <- evans_flatlist %>% filter(papername != "NA") %>%
ggplot()+
geom_point(aes(FWHM_median, FWHM_sd, fill = papername), pch=24, size=4)+
scale_fill_manual(values = c("#782281", "#EA5661", "#FDE0A1"))+
scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,12))+
xlab(TeX("median value of of FWHM $\\(cm^{-1})$"))+
ylab(TeX("standard deviation of FWHM $\\(cm^{-1})$")) +
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
legend.position = "none",
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
evans_grain_summary
#Figure 2c
pikes_violin <- pikes_data %>%
ggplot()+
geom_violin(aes(papername, FWHM, fill = papername), scale = "count", draw_quantiles = c(0.25, 0.5, 0.75))+
scale_fill_manual(values = c("#000004", "#7D2482", "#FD9A6A"))+
scale_y_continuous(expand = c(0,0), limits = c(0,36))+
ylab(TeX('$\\FWHM (cm^{-1})')) +
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
legend.position = "none",
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
print(pikes_violin)
#Figure 2d
pikes_grain_summary <- pikes_flatlist %>% filter(papername != "NA") %>%
ggplot()+
geom_point(aes(FWHM_median, FWHM_sd, fill = papername), pch=22, size=4)+
scale_fill_manual(values = c("#000004", "#7D2482", "#FD9A6A"))+scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,12))+
geom_point(data = dated_grains, aes( FWHM_median, FWHM_sd), color = "white", pch =16, size =1) +
xlab(TeX("median value of of FWHM $\\(cm^{-1})$"))+
ylab(TeX("standard deviation of FWHM $\\(cm^{-1})$")) +
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
legend.position = "none",
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
pikes_grain_summary
## Warning: Removed 15 rows containing missing values (geom_point).
Supplementary text figures
Figure S6
#PP1
PP1_zhe <- pikes_zhe %>%
mutate (
fullname = paste(papername, Grain)
) %>%
filter(fullname == "PP1 z23" | fullname == "PP1 z31" | fullname == "PP1 z32" | fullname == "PP1 z33" | fullname == "PP1 z36")
PP1_raman <- pikes_data %>%
filter(papername == "PP1") %>%
mutate(
Grain =
ifelse(grain == "23", "z23",
ifelse(grain == 31, "z31",
ifelse(grain == 32, "z32",
ifelse(grain == 33, "z33",
ifelse(grain== 36, "z36", NA
)
)
)
)
)
) %>%
mutate (fullname = paste(papername, Grain)) %>%
filter(fullname == "PP1 z23" | fullname == "PP1 z31" | fullname == "PP1 z32" | fullname == "PP1 z33" | fullname == "PP1 z36")
PP1_all <- left_join(PP1_raman, PP1_zhe, by = "fullname")
PP1_zhevsFWHM <- PP1_all %>% ggplot()+
aes(x = FWHM, y = Corr_Date, shape = fullname, fill = Sample) +
geom_point(size = 4)+
scale_shape_manual(values = c(21, 22, 23, 24, 25))+
scale_fill_manual(values = c("#000004"))+
scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,800))+
xlab(TeX('$\\FWHM (cm^{-1})')) +
ylab ("Zhe Date (Ma)")+
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
print(PP1_zhevsFWHM)
PP1_eUvsFWHM <- PP1_all %>% ggplot()+
aes(x = FWHM, y = eU, shape = fullname, fill = Sample) +
geom_point(size = 4)+
scale_shape_manual(values = c(21, 22, 23, 24, 25))+
scale_fill_manual(values = c("#000004"))+
scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,800))+
xlab(TeX('$\\FWHM (cm^{-1})')) +
ylab ("Zhe eU (ppm)")+
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
print(PP1_eUvsFWHM)
## Warning: Removed 11 rows containing missing values (geom_point).
#PP3
PP3_zhe <- pikes_zhe %>%
mutate (
fullname = paste(papername, Grain)
) %>%
filter(fullname == "PP3 z17" | fullname == "PP3 z21" | fullname == "PP3 z27")
PP3_raman <- pikes_data %>%
filter(papername == "PP3") %>%
mutate(
Grain =
ifelse(grain == "17", "z17",
ifelse(grain == 21, "z21",
ifelse(grain == 27, "z27", NA
)
)
)
) %>%
mutate (fullname = paste(papername, Grain)) %>%
filter(fullname == "PP3 z17" | fullname == "PP3 z21" | fullname == "PP3 z27")
PP3_all <- left_join(PP3_raman, PP3_zhe, by = "fullname")
PP3_zhevsFWHM <- PP3_all %>% ggplot()+
aes(x = FWHM, y = Corr_Date, shape = fullname, fill = Sample) +
geom_point(size = 4)+
scale_shape_manual(values = c( 22, 24, 25))+
scale_fill_manual(values = c("#7D2482"))+
scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,800))+
xlab(TeX('$\\FWHM (cm^{-1})')) +
ylab ("Zhe Date (Ma)")+
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
print(PP3_zhevsFWHM)
PP3_eUvsFWHM <- PP3_all %>% ggplot()+
aes(x = FWHM, y = eU, shape = fullname, fill = Sample) +
geom_point(size = 4)+
scale_shape_manual(values = c( 22, 24, 25))+
scale_fill_manual(values = c("#7D2482"))+
scale_x_continuous(expand = c(0,0), limits = c(0,36))+
scale_y_continuous(expand = c(0,0), limits = c(0,800))+
xlab(TeX('$\\FWHM (cm^{-1})')) +
ylab ("Zhe eU (ppm)")+
theme_classic()+
theme(
panel.border=element_rect(fill=NA,size = 1),
text = element_text(size = 12),
axis.ticks = element_line(color="black"),
axis.line = element_line(color = NA),
axis.text.y = element_text(color = "black", size = 12),
axis.text.x = element_text (color = "black", size = 12),
axis.title.x = element_blank()
)
print(PP3_eUvsFWHM)
